Hi @Nafeeza86 -
I suppose the answer is “it depends”. What kind of prediction are you doing? Is this a classification model, or forecasting with time series, or…?
If you are using 4 years of data for training and 1 for testing, regardless of the amount of time encompassed, they key question is this: how similar is your new, unknown data to the data you built your model with? You might have an idea about this up front, but you probably won’t be able to know for sure. So the modeling process will probably be iterative, and involve looking at how well predictions on your new dataset go, and how future predictions accuracy might (or might not ) decay over time.
Sorry that my answer lacks specifics. At any rate, start small with your predictions - maybe a few months or a year - and then extend your time horizon if the model performs well.